8 papers
MHE-Former: Multi-Hypothesis Transformers via Entropy Maximization for 3D Mesh Recovery
Boshu Jia, Rongyu Chen, Linlin Yang +9
Monocular 3D hand and body mesh recovery often suffers from severe occlusion and ambiguity. Traditional deterministic methods typically regress a single optimal solution, leading t…
What Matters for Latent Actions in Robot Learning
Xizhou Bu, Qingda Hu, Lei Zhou +13
Latent Action Models (LAMs) have emerged as a promising paradigm for enabling robot learning to leverage large-scale unlabeled videos through latent actions that serve as compact s…
VidForensics-M1: Meta-Detection Reinforcement Learning with Verifiable Temporal Grounding for AI-Generated Video Forensics
Bowei Liu, Zheng Lu, Yuhan Bian +8
Recent advances in video generation models have significantly improved the realism of synthetic videos, blurring the boundary between generated and authentic content and raising co…
Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation
Jie Zhang, Xiaoyue Chen, Anzhe Chen +36
We introduce Qwen-RobotWorld, a language-conditioned video world model for embodied intelligence. With natural language as a unified action interface, it predicts physically ground…
ESOM: Efficiently Understanding Streaming Video Anomalies with Open-world Dynamic Definitions
Zihao Liu, Xiaoyu Wu, Wenna Li +2
Open-world video anomaly detection (OWVAD) aims to detect and explain abnormal events under different anomaly definitions, which is important for applications such as intelligent s…
MLVTG: Mamba-Based Feature Alignment and LLM-Driven Purification for Multi-Modal Video Temporal Grounding
Zhiyi Zhu, Xiaoyu Wu, Zihao Liu +1
Video Temporal Grounding (VTG), which aims to localize video clips corresponding to natural language queries, is a fundamental yet challenging task in video understanding. Existing…
Rethinking Metrics and Benchmarks of Video Anomaly Detection
Zihao Liu, Xiaoyu Wu, Wenna Li +2
Video Anomaly Detection (VAD), which aims to detect anomalies that deviate from expectation, has attracted increasing attention in recent years. Existing advancements in VAD primar…
Language-guided Open-world Video Anomaly Detection under Weak Supervision
Zihao Liu, Xiaoyu Wu, Jianqin Wu +2
Video anomaly detection (VAD) aims to detect anomalies that deviate from what is expected. In open-world scenarios, the expected events may change as requirements change. For examp…